PROJECT SUMMARY Mutations in the serine/threonine kinase Cyclin-Dependent Kinase-Like 5 (CDKL5) are strongly implicated in infantile epileptic encephalopathy (IEE), yet at present only a few substrates have been identified, and the mechanisms behind CDKL5 mutation in disease etiology remains largely unknown. Until these knowledge gaps are addressed, it is likely that the field will struggle to understand, and have difficulty treating, CDKL5- associated IEE. The long-term goal is to understand the fundamental mechanisms behind infantile epileptic encephalopathy, in order to develop new, effective therapeutic strategies. This requires a precise understanding of the role(s) of CDKL5 in both normal brain development and IEE. The objective in this application, therefore, is to identify the substrate specificity of wild-type and mutant CDKL5, and to create publically accessible CDKL5 substrate predictors. The central hypothesis is that IEE-associated CDKL5 mutations will rewire kinase substrate specificity, resulting in distinct substrate pools for individual CDKL5 variants. This hypothesis has been formulated based on preliminary data from the applicant's laboratory. The rationale underlying the proposed research is that characterizing the substrate specificity of wild-type and IEE- associated CDKL5 mutants, and creating freely available tools that use this data to identify high-confidence putative substrates, will allow the field to advance the understanding of CDKL5-associated encephalopathy. Guided by strong preliminary data, the central hypothesis will be tested through the first of two specific aims: 1) Identify the wild-type and encephalopathy-associated mutant substrate specificities of the CDKL5 kinase; the critical need for accessible prediction tools will be addressed in the second specific aim: 2) Create freely accessible, custom substrate predictors for each CDKL5 variant. The first aim will be conducted using a novel bacterial approach for determining protein kinase specificity, while the second aim will be accomplished by a companion computational tool for substrate prediction; both the bacterial approach and computational tool were pioneered by the applicant's group. The proposed research is innovative, in the applicant's opinion, because it combines their lab's approach for specificity determination with powerful computational tools, and represents a significant departure from the status quo by shifting the focus of CDKL5 disease etiology to substrate specificity rewiring. The research will be significant because it is expected to offer critical insight into the etiology of CDKL5-associated IEE. Ultimately, this insight has the potential to guide the treatment of IEE, and inform the development of novel therapeutic strategies.